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CVPR
2012
IEEE
11 years 10 months ago
Adaptive object tracking by learning background context
One challenge when tracking objects is to adapt the object representation depending on the scene context to account for changes in illumination, coloring, scaling, etc. Here, we p...
Ali Borji, Simone Frintrop, Dicky N. Sihite, Laure...
NAACL
2010
13 years 5 months ago
Unsupervised Model Adaptation using Information-Theoretic Criterion
In this paper we propose a novel general framework for unsupervised model adaptation. Our method is based on entropy which has been used previously as a regularizer in semi-superv...
Ariya Rastrow, Frederick Jelinek, Abhinav Sethy, B...
WWW
2004
ACM
14 years 8 months ago
Authoring of learning styles in adaptive hypermedia: problems and solutions
Learning styles, as well as the best ways of responding with corresponding instructional strategies, have been intensively studied in the classical educational (classroom) setting...
Natalia Stash, Alexandra I. Cristea, Paul De Bra
AAAI
2008
13 years 10 months ago
Adaptive Treatment of Epilepsy via Batch-mode Reinforcement Learning
This paper highlights the crucial role that modern machine learning techniques can play in the optimization of treatment strategies for patients with chronic disorders. In particu...
Arthur Guez, Robert D. Vincent, Massimo Avoli, Joe...
GI
2007
Springer
14 years 1 months ago
Background Modeling Using Adaptive Cluster Density Estimation for Automatic Human Detection
: Detection is an inherent part of every advanced automatic tracking system. In this work we focus on automatic detection of humans by enhanced background subtraction. Background s...
Harish Bhaskar, Lyudmila Mihaylova, Simon Maskell